
Databricks: Leading Data and AI Platform for Enterprises
What is Databricks? Databricks is a unified data and AI platform that runs both analytical and operational workloads on one open, governed foundation.
Databricks - Wikipedia
Databricks, Inc. is an American software company based in San Francisco. [4] It was founded in 2013 by the original creators of Apache Spark at the University of California, Berkeley. [1][5] It offers a cloud …
What is Azure Databricks? - Azure Databricks | Microsoft Learn
Jun 11, 2026 · Azure Databricks combines user-friendly UIs with cost-effective compute resources and infinitely scalable, affordable storage to provide a powerful platform for running analytic queries.
About Databricks: The data and AI company
Headquartered in San Francisco, with offices around the world, Databricks is on a mission to simplify and democratize data and AI, helping data and AI teams solve the world’s toughest problems.
Azure Databricks | Microsoft Azure
Explore Azure Databricks, a managed service for open data lakehouses. Power your data analytics and AI strategy with an intelligent data platform on Azure.
What is - Databricks on AWS
Jun 11, 2026 · Databricks combines the power of Apache Spark with Delta and custom tools to provide an unrivaled ETL experience. Use SQL, Python, and Scala to compose ETL logic and orchestrate …
Learn Databricks - Training & Resources | Databricks
Explore Databricks resources for data and AI, including training, certification, events, and community support to enhance your skills.
IPO-bound Databricks reportedly eyes $175B valuation after hitting $5 ...
Jun 9, 2026 · Databricks has discussed raising fresh funding at a valuation of $165B–$175B, with a new round potentially starting as soon as next month.
Databricks Reviews (1,623): Pros & Cons of Working At Databricks
1,623 Databricks reviews. A free inside look at company reviews and salaries posted anonymously by employees.
Azure Databricks documentation | Microsoft Learn
Learn Azure Databricks, a unified analytics platform for data analysts, data engineers, data scientists, and machine learning engineers.